Currently, the general radio resource management of wireless multimedia communication network mainly contains the channel and transmit power assignments, which are stated hereinafter.
A previous study has proposed an adaptive neural fuzzy inference system (ANFIS)-assisted power control scheme for a multi-rate multimedia direct-sequence code-division multiple-access (DS-CDMA) system to precisely predict the channel variations and thus compensate for the effect of signal fading in advance [1]. The author in the above study also provides a procedure for determining the transmission rate based upon the output of the signal-to-interference and noise ratio (SINR) increment of the ANFIS power control mechanisms at the sample period. The fuzzy membership functions of ANFIS power control mechanisms use seven Gaussian functions, so that there are 49 fuzzy inference rules. The ANFIS power control mechanisms use two input variables, including SINR error e(n) and SINR error change Δe(n), to track the set point of target SINR. In the present technique, the target SINR value is set to a fix value of 1.5 dB, let the power control process is not flexible enough. The input parameters of ANFIS power control mechanism totally depend on SINR control efficiency. The power cannot be controlled by channel environment and user speed change. The technology has not considered network traffic performance and user speed. According to the method used in another study [2], the neural fuzzy call-admission and rate controller (NFCRC) takes the handoff failure probability and the resource availability of the selected cell as input variables of the ANFIS to guarantee the QoS requirement of handoff failure probability for all traffic loads, but the new call blocking probability is higher than 0.05. The buffer size in the given cell is assumed to be three for new and handoff calls so that the system can wait for the channel to become available before dropping the call    [1] C. H. Jiang, J. K. Lian, R. M. Weng, C. H. Hsu, “Multi-rate DS-CDMA with ANFIS-assisted power control for wireless multi-media communications,” International Journal of Innovative Computing, Information and Control, vol. 6, no. 8, pp. 3641-3655, August 2010.    [2] K. R. LO, C. J. Chang, C. B. Shung, “A neural fuzzy resource manager for hierarchical cellular systems supporting multimedia services,” IEEE Trans. on Vehicular Tech., vol. 52, no. 5, pp. 1196-1206, September 2003.